Prognosis following a diagnosis of primary lung cancer remains very poor; individualized treatment plans according to predicted responses and subsequent survivorship are needed. As an effort to meet this challenge, we have been investigating genetic variations in the human glutathione metabolic system as one of the promising candidates to predict platinum-based treatment outcomes and survival. Six polymorphic DMA markers were tested as proposed. Our data to-date, based on 803 non-small cell lung cancer patients, support the hypothesis that patient survival after platinum-based therapy may be predicted by the glutathione system genotypes. In this renewal application, we propose to accomplish three aims: 1) In-depth evaluation of the host genetic variations on prognosis among patients with advanced stage lung cancer at three levels of outcome: treatment response, prominent adverse drug reactions, and overall and lung cancer-free survival. Two specific expansions to the original study scope are the addition of other important genetic polymorphisms and three additional drug groups that are used in combination with or independently of platinum-based drugs (taxanes, gemcitabine, and epidermal growth factor inhibitors). 2) Because ionizing radiation (radiotherapy) is also commonly used in treating advanced stage lung cancer and often combined with chemotherapy, we will expand our investigation to radiation therapy in relation to treatment response, prominent dose-limiting adverse reactions, and survival. Host genetic variations in the mechanistic pathways of radiation therapy will be studied in parallel to Aim 1. We aim to identify and assess the roles of genetic variations influencing these mechanisms in developing radiotherapy related lung and esophageal damage. 3) We will examine the effects of multiple prognostic factors that have been previously reported and discovered by our team and in the literature. The main and interactive effects of genetic variations responsible for varied responses to chemotherapy and/or radiation therapy and of these other prognostic factors will be systematically evaluated using multivariate models and analyses. Our ambitious yet feasible goal is accomplishable by capitalizing on our established resource that has been supported through a R03 and three R01 grants (with non-overlapping research theme) awarded to our research team over the past 8 years. We anticipate enrolling at least 1100 stage 11 I/I V non-small cell and 400 small cell lung cancer patients. Results from this pharmacogenetic and molecular epidemiology study may suggest new directions to enhance clinical management and to improve survivorship of lung cancer patients. Our ultimate goal is to build comprehensive and clinically useful models in designing patient-specific treatment plans and in predicting patients' treatment response and survival.